scholarly journals Automatic Determination of Vertical Cup-to-Disc Ratio in Retinal Fundus Images for Glaucoma Screening

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 8527-8541 ◽  
Author(s):  
Jiapan Guo ◽  
George Azzopardi ◽  
Chenyu Shi ◽  
Nomdo M. Jansonius ◽  
Nicolai Petkov
Keyword(s):  
Fundus Images ◽  
Automatic Determination ◽  
Glaucoma Screening ◽  
Retinal Fundus Images ◽  
Retinal Fundus ◽  
Cup To Disc Ratio

scholarly journals Automated detection of optic disc in retinal fundus images using gabor filter kernels

2015 ◽  
Vol 5 (1) ◽  
pp. 36
Author(s):  
Baha Sen ◽  
Kemal Akyol ◽  
Safak Bayir ◽  
Hilal Kaya
Keyword(s):  
Diabetic Retinopathy ◽  
Optic Disc ◽  
Retinal Image ◽  
Gabor Filter ◽  
Blue Color ◽  
Fundus Images ◽  
Automatic Determination ◽  
Retinal Fundus Images ◽  
Retinal Fundus

<p>Identifying the position of the optic disc on the retinal fundus image is a technique that is often used in medical diagnosis, treatment and monitoring processes. Determination of the intensity of the bright colors that belongs to the optic disc on a normal retinal image by the help of image processing algorithms is a fairly easy process. However, determining the optic disc on a retinal image including the diabetic retinopathy disease is a more difficult process. The reason for this difficulty is the existence of many regions that have the same light intensity in different parts of the retina. In this study, a new method for supplying the automatic determination of the optic disc in a recursive manner is proposed. By the help of OpenCV library, automatic determination process of the optic disc on the retinal fundus images including the diabetic retinopathy disease, has been implemented. Circular regions with maximum brightness values in the retinal images that were normalized and passed through the denoising process were determined and these regions were analyzed if they are optic disc or not. This process basically consists of two steps: In the first step, the possible optic disc candidate regions were determined recursively and in the second step, by the help of Gabor filter kernels, these regions were analyzed and it’s provided to decide if they are optic disc or not. This study is based on a dataset that has 89 images including diabetic retinopathy disease. Performance of this system is tested on these images and also on the images that the red, green, blue color channels and Contrast Limited Adaptive Histogram Equalization (CLAHE) retinas were obtained. Most accurate determination of the position of the optic disc is obtained with retinas, implemented process CLAHE, including the best success rate of 89.88%.</p><p> </p>Keywords: Optic disc, diabetic retinopathy, recursively, circular region, gabor filter kernels.

Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images

2011 ◽  
Vol 16 (9) ◽  
pp. 096009 ◽  
Author(s):  
Chisako Muramatsu ◽  
Toshiaki Nakagawa ◽  
Akira Sawada ◽  
Yuji Hatanaka ◽  
Tetsuya Yamamoto ◽  
...  
Keyword(s):  
Fundus Images ◽  
Retinal Fundus Images ◽  
Retinal Fundus ◽  
Automated Determination ◽  
Cup To Disc Ratio

scholarly journals An Automatic Image Processing System for Glaucoma Screening

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Ahmed Almazroa ◽  
Sami Alodhayb ◽  
Kaamran Raahemifar ◽  
Vasudevan Lakshminarayanan
Keyword(s):  
Image Processing ◽  
Optic Nerve ◽  
Processing System ◽  
Fundus Images ◽  
Type Ii ◽  
Fuzzy Approach ◽  
Glaucoma Screening ◽  
Automatic Image Processing ◽  
Retinal Fundus Images ◽  
Retinal Fundus

Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma’s population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm’s accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm’s accuracy. The algorithm’s best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.

scholarly journals Automated Glaucoma Screening in Retinal Fundus Images

2015 ◽  
Vol 10 (9) ◽  
pp. 129-136 ◽  
Author(s):  
Srinivasan Aruchamy ◽  
Partha Bhattacharjee ◽  
Goutam Sanyal
Keyword(s):  
Fundus Images ◽  
Glaucoma Screening ◽  
Retinal Fundus Images ◽  
Retinal Fundus
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